1. Field of the Invention
This invention relates to a method of compressing image signals by vector quantization. This invention particularly relates to a method of compressing image signals by vector quantization, wherein generation of block distortion in a reconstructed image is prevented.
2. Description of the Prior Art
Image signals representing half tone images, such as television signals, are composed of enormous amounts of information, and a broad-band transmission line is required for transmission of the image signals. Such image signals involve much redundancy, and various attempts have been made to compress the image signals by restricting the redundancy. Also, in recent years, recording of half tone images on optical disks, magnetic disks, or the like has been generally put into practice. In this case, image signal compression is conducted generally for the purpose of efficiently recording image signals on a recording medium.
One of the methods of image signal compression that has heretofore been known is a method wherein vector quantization is utilized. The known method comprises the steps of (i) dividing two-dimensional image signals into blocks each comprising the signals at M number of picture elements adjacent to one another, (ii) selecting a vector that corresponds with the minimum distortion to the set of the image signals in each of the blocks from a code book comprising a plurality of vectors different from one another and prepared in advance by defining M number of vector elements, and (iii) encoding the information representing the selected vector to correspond to the block.
Since the image signals in the block as mentioned above have high correlation therebetween, the image signals in each block can be represented very accurately by one of a comparatively small number of vectors prepared in advance. Therefore, transmission or recording of the image signals can be carried out by transmitting or recording a code representing the vector, instead of the image signals themselves, and signal compression can thus be achieved. By way of example, the amount of the image signals at 64 picture elements in a half tone image of a density scale composed of 256 levels (=8 bits) is 8.times.64=512 bits. In the case where the 64 picture elements are grouped as a single block, the respective image signals in the block are expressed by a vector composed of 64 vector elements, and a code book including 256 such vectors is prepared, the amount of the signals per block becomes equal to the amount of the signals for discrimination between the vectors, i.e. 8 bits. Consequently, in this case, the amount of the signals can be compressed to 1/64.
After the image signals are compressed in the manner as mentioned above and recorded or transmitted in the compressed form, the vector elements of each of the vectors which the vector discriminating information represents are taken as reconstructed signals of each of the blocks, and the original image is reproduced by use of the reconstructed signals.
With the aforesaid method of compressing image signals, the vector discriminating information can be expressed with a shorter code length and the signal compressibility can be increased as the number of the vectors prepared in advance is smaller. Therefore, there have heretofore been proposed the methods of compressing image signals wherein the signal compressibility is improved from the aforesaid viewpoint by further advancing the vector quantization.
As such methods of compressing image signals, there have heretofore been known a technique of representative value separation type vector quantization and a technique of vector quantization of interpolation prediction errors. The former technique comprises the steps of calculating a representative value m (for example, a mean value) of the image signals in each block, selecting a vector whose vector elements correspond with the minimum distortion to differences (x.sub.1 -m, x.sub.2 -m, x.sub.3 -m, . . . , x.sub.M -m) between the respective image signals in the block and the representative value m from a code book, and encoding the vector discriminating information together with the information representing the representative value m.
The fluctuation width of the differences (xi-m) becomes smaller than the fluctuation width of the original image signals xi, and therefore the number of vectors which are to be prepared in advance, i.e. the size of the code book, may be small.
On the other hand, the technique of vector quantization of interpolation prediction errors comprises the steps of carrying out interpolation prediction of the image signals in each block in an appropriate manner, selecting a vector that correspond with the minimum distortion to the errors, i.e. the interpolation prediction errors, (x.sub.1 -x.sub.1, x.sub.2 -x.sub.2, x.sub.3 -x.sub.3, ..., x.sub.M -x.sub.M) between the actual image signals xi and the interpolation-predicted values xi from a code book, and encoding the vector discriminating information together with the information utilized for the interpolation prediction. Also, in this case, the fluctuation width of the interpolation prediction errors (xi-xi) becomes smaller than the fluctuation width of the original image signals xi, and therefore the number of vectors which are to be prepared in advance may be small. In both the representative value separation type vector quantization and the vector quantization of the interpolation prediction errors, the signals may be normalized.
In the course of reconstructing the image after compressing the image signals by the aforesaid advanced type vector quantization, the values obtained by adding the representative value m or the interpolation-predicted values x to the vector elements of the vector which the vector discriminating information represents may be used as the reconstructed signals, and the image may be reproduced on the basis of the reconstructed signals.
However, in the reconstructed image obtained in the manner as mentioned above, block distortion, i.e. a difference in density at the boundary between the blocks, readily arises.